updates

Author: sayakpaul

src/diffusers/loaders/lora_base.py

@@ -906,7 +906,7 @@ def save_function(weights, filename):
                     # We need to be able to serialize the NoneTypes too, otherwise we run into
                     # 'NoneType' object cannot be converted to 'PyString'
                     metadata = {"format": "pt"}
-                    if lora_adapter_metadata is not None:
+                    if lora_adapter_metadata:
                         for key, value in lora_adapter_metadata.items():
                             if isinstance(value, set):
                                 lora_adapter_metadata[key] = list(value)

src/diffusers/loaders/lora_pipeline.py

@@ -1695,10 +1695,9 @@ def save_lora_weights(
         if not transformer_lora_layers:
             raise ValueError("You must pass `transformer_lora_layers`.")
 
-        if transformer_lora_layers:
-            state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
+        state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
 
-        if transformer_lora_adapter_metadata:
+        if transformer_lora_adapter_metadata is not None:
             lora_adapter_metadata.update(cls.pack_weights(transformer_lora_adapter_metadata, cls.transformer_name))
 
         # Save the model
@@ -3020,10 +3019,9 @@ def save_lora_weights(
         if not transformer_lora_layers:
             raise ValueError("You must pass `transformer_lora_layers`.")
 
-        if transformer_lora_layers:
-            state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
+        state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
 
-        if transformer_lora_adapter_metadata:
+        if transformer_lora_adapter_metadata is not None:
             lora_adapter_metadata.update(cls.pack_weights(transformer_lora_adapter_metadata, cls.transformer_name))
 
         # Save the model
@@ -3344,10 +3342,9 @@ def save_lora_weights(
         if not transformer_lora_layers:
             raise ValueError("You must pass `transformer_lora_layers`.")
 
-        if transformer_lora_layers:
-            state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
+        state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
 
-        if transformer_lora_adapter_metadata:
+        if transformer_lora_adapter_metadata is not None:
             lora_adapter_metadata.update(cls.pack_weights(transformer_lora_adapter_metadata, cls.transformer_name))
 
         # Save the model
@@ -3670,10 +3667,9 @@ def save_lora_weights(
         if not transformer_lora_layers:
             raise ValueError("You must pass `transformer_lora_layers`.")
 
-        if transformer_lora_layers:
-            state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
+        state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
 
-        if transformer_lora_adapter_metadata:
+        if transformer_lora_adapter_metadata is not None:
             lora_adapter_metadata.update(cls.pack_weights(transformer_lora_adapter_metadata, cls.transformer_name))
 
         # Save the model
@@ -3996,10 +3992,9 @@ def save_lora_weights(
         if not transformer_lora_layers:
             raise ValueError("You must pass `transformer_lora_layers`.")
 
-        if transformer_lora_layers:
-            state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
+        state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
 
-        if transformer_lora_adapter_metadata:
+        if transformer_lora_adapter_metadata is not None:
             lora_adapter_metadata.update(cls.pack_weights(transformer_lora_adapter_metadata, cls.transformer_name))
 
         # Save the model
@@ -4325,10 +4320,9 @@ def save_lora_weights(
         if not transformer_lora_layers:
             raise ValueError("You must pass `transformer_lora_layers`.")
 
-        if transformer_lora_layers:
-            state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
+        state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
 
-        if transformer_lora_adapter_metadata:
+        if transformer_lora_adapter_metadata is not None:
             lora_adapter_metadata.update(cls.pack_weights(transformer_lora_adapter_metadata, cls.transformer_name))
 
         # Save the model
@@ -4655,10 +4649,9 @@ def save_lora_weights(
         if not transformer_lora_layers:
             raise ValueError("You must pass `transformer_lora_layers`.")
 
-        if transformer_lora_layers:
-            state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
+        state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
 
-        if transformer_lora_adapter_metadata:
+        if transformer_lora_adapter_metadata is not None:
             lora_adapter_metadata.update(cls.pack_weights(transformer_lora_adapter_metadata, cls.transformer_name))
 
         # Save the model
@@ -5014,10 +5007,9 @@ def save_lora_weights(
         if not transformer_lora_layers:
             raise ValueError("You must pass `transformer_lora_layers`.")
 
-        if transformer_lora_layers:
-            state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
+        state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
 
-        if transformer_lora_adapter_metadata:
+        if transformer_lora_adapter_metadata is not None:
             lora_adapter_metadata.update(cls.pack_weights(transformer_lora_adapter_metadata, cls.transformer_name))
 
         # Save the model
@@ -5340,10 +5332,9 @@ def save_lora_weights(
         if not transformer_lora_layers:
             raise ValueError("You must pass `transformer_lora_layers`.")
 
-        if transformer_lora_layers:
-            state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
+        state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
 
-        if transformer_lora_adapter_metadata:
+        if transformer_lora_adapter_metadata is not None:
             lora_adapter_metadata.update(cls.pack_weights(transformer_lora_adapter_metadata, cls.transformer_name))
 
         # Save the model
@@ -5666,10 +5657,9 @@ def save_lora_weights(
         if not transformer_lora_layers:
             raise ValueError("You must pass `transformer_lora_layers`.")
 
-        if transformer_lora_layers:
-            state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
+        state_dict.update(cls.pack_weights(transformer_lora_layers, cls.transformer_name))
 
-        if transformer_lora_adapter_metadata:
+        if transformer_lora_adapter_metadata is not None:
             lora_adapter_metadata.update(cls.pack_weights(transformer_lora_adapter_metadata, cls.transformer_name))
 
         # Save the model

src/diffusers/utils/peft_utils.py

@@ -158,9 +158,10 @@ def get_peft_kwargs(
 
     if LORA_ADAPTER_METADATA_KEY in peft_state_dict:
         metadata = peft_state_dict[LORA_ADAPTER_METADATA_KEY]
-        if prefix is not None:
-            metadata = {k.replace(f"{prefix}.", ""): v for k, v in metadata.items()}
-        return metadata
+        if metadata:
+            if prefix is not None:
+                metadata = {k.replace(f"{prefix}.", ""): v for k, v in metadata.items()}
+            return metadata
 
     rank_pattern = {}
     alpha_pattern = {}